AIOps: A Beginners Guide - Part 1
August 15, 2022

Vinay Chandrasekhar
Elastic

Share this

Artificial Intelligence for IT Operations (or AIOps for short) continues to be a hot topic among developers, SREs, or DevOps professionals. The case for AIOps is especially crucial given the expansive nature of today's observability efforts across hybrid and multi-cloud environments. As with most observability challenges, AIOps starts with telemetry data: metrics, logs, traces, and events.

Once IT operations teams collect and begin to analyze the data, the benefit of AIOps becomes rapidly clear. AIOps aims to accurately and proactively identify areas that need attention and assist IT teams in solving issues faster. As human beings, we cannot keep up with analyzing petabytes of raw observability data. Adding AIOps delivers a layer of intelligence via analytics and automation to help reduce overhead for a team. Let's dive in to answer common questions on this critical topic.


What Is AIOps and How Can It Help Me?

Simply put, AIOps is the ability of software systems to ease and assist IT operations via the use of AI/ML and related analytical technologies. AIOps capabilities can be applied to various operational data, including ingestion and processing of log data, traces, metrics, and much more.

Seeking to clarify the often murky and confusing world of AIOps are Gartner, Forrester and others who provide market definition. AIOps can help significantly reduce the time and effort to detect, understand, investigate, determine root cause, and remediate issues and incidents faster. Saving time during troubleshooting can, in turn, help IT personnel focus more of their energy on higher-value tasks and projects.

Why Do You Need AIOps as Part of Your Observability Strategy?

Many recent articles (Gartner glossary for AIOps, Forrester AIOps reports) describe the dynamics in the IT market. From digital transformation initiatives to cloud migration to distributed, hybrid, or cloud-native application deployments, these dynamics are dramatically changing the IT operations landscape.

The landscape changes have the following three characteristics:

Data volume: The volume of data for observability continues to increase exponentially.

Complexity: Applications, workloads, and deployments continue to become more complex, ephemeral, and distributed.

Pace of change: The rate at which changes (application and infrastructure) occur is faster than ever before.

These are not mutually exclusive. In some ways, quite the opposite. For example, high rates of change and complex deployments utilizing auto-scaling mean an even higher volume of data. This increasing complexity means that humans will depend on systems and automation to keep up with the changes. For this reason, AIOps will play a key role in responding to these operational and business challenges.

Leveraging AI/ML to roll up data, summarize it, and intelligently tier the data for storage can help alleviate some of the volume challenges. Explicit visual depictions of an application environment (infrastructure and service dependency maps) and contextual navigation help align troubleshooting efforts with how users think of their deployment. Furthermore, auto-surfacing of problems and root causes analyses will address some of the other complex challenges.

Observability products will need to keep track of all application and infrastructure changes and correlate those changes with system behavior and user experience because change is often the root cause of acute, anomalous behavior. An upgrade or patch for a new feature with unintended consequences is a typical example. Enabling those correlations helps teams be more agile and adept at keeping pace with those frequent changes helping sustain service performance.

AIOps play a key role and can help navigate these challenges effectively, freeing up operations teams to focus on more important work when properly implemented and used.

Which Observability Use Cases Are Best for AIOps?

Several observability workflows and use cases are already very well served with the application of AIOps techniques and technologies, for example:

■ Service degradation such as sudden or unexpected variations in latency can be detected via anomaly detection.

■ Massive volumes of data, such as unstructured or semi-structured log messages, can be automatically classified, categorized, and summarized to help ease consumption and analysis.

■ Multiple symptoms, events, and issues can be correlated to help cut down alert "noise" and reduce time to root cause determination.

■ Automatic health scoring based on an assessment of impact, the extent of anomalies, and other measures help surface the most critical issues first, further reducing noise.

In the more well-understood and time-tested "if this is the symptom, then this is the likely root cause" relationships, AIOps can help automatically look for, detect, and classify those symptoms and surface those potential root causes. Ultimately, AIOps can enable remediation actions to fix routine or trivial issues and reduce burnout for operations teams

In a future blog, we will dive deeper into key use cases and how you can identify scenarios to apply AIOps in day-to-day operations.

Vinay Chandrasekhar is Sr. Principal Product Manager, Observability, at Elastic
Share this

The Latest

October 03, 2022

IT engineers and executives are responsible for system reliability and availability. The volume of data can make it hard to be proactive and fix issues quickly. With over a decade of experience in the field, I know the importance of IT operations analytics and how it can help identify incidents and enable agile responses ...

September 30, 2022

For businesses with vast and distributed computing infrastructures, one of the main objectives of IT and network operations is to locate the cause of a service condition that is having an impact. The more human resources are put into the task of gathering, processing, and finally visual monitoring the massive volumes of event and log data that serve as the main source of symptomatic indications for emerging crises, the closer the service is to the company's source of revenue ...

September 29, 2022

Our digital economy is intolerant of downtime. But consumers haven't just come to expect always-on digital apps and services. They also expect continuous innovation, new functionality and lightening fast response times. Organizations have taken note, investing heavily in teams and tools that supposedly increase uptime and free resources for innovation. But leaders have not realized this "throw money at the problem" approach to monitoring is burning through resources without much improvement in availability outcomes ...

September 28, 2022

Although 83% of businesses are concerned about a recession in 2023, B2B tech marketers can look forward to growth — 51% of organizations plan to increase IT budgets in 2023 vs. a narrow 6% that plan to reduce their spend, according to the 2023 State of IT report from Spiceworks Ziff Davis ...

September 27, 2022

Users have high expectations around applications — quick loading times, look and feel visually advanced, with feature-rich content, video streaming, and multimedia capabilities — all of these devour network bandwidth. With millions of users accessing applications and mobile apps from multiple devices, most companies today generate seemingly unmanageable volumes of data and traffic on their networks ...

September 26, 2022

In Italy, it is customary to treat wine as part of the meal ... Too often, testing is treated with the same reverence as the post-meal task of loading the dishwasher, when it should be treated like an elegant wine pairing ...

September 23, 2022

In order to properly sort through all monitoring noise and identify true problems, their causes, and to prioritize them for response by the IT team, they have created and built a revolutionary new system using a meta-cognitive model ...

September 22, 2022

As we shift further into a digital-first world, where having a reliable online experience becomes more essential, Site Reliability Engineers remain in-demand among organizations of all sizes ... This diverse set of skills and values can be difficult to interview for. In this blog, we'll get you started with some example questions and processes to find your ideal SRE ...

September 21, 2022

US government agencies are bringing more of their employees back into the office and implementing hybrid work schedules, but federal workers are worried that their agencies' IT architectures aren't built to handle the "new normal." They fear that the reactive, manual methods used by the current systems in dealing with user, IT architecture and application problems will degrade the user experience and negatively affect productivity. In fact, according to a recent survey, many federal employees are concerned that they won't work as effectively back in the office as they did at home ...

September 20, 2022

Users today expect a seamless, uninterrupted experience when interacting with their web and mobile apps. Their expectations have continued to grow in tandem with their appetite for new features and consistent updates. Mobile apps have responded by increasing their release cadence by up to 40%, releasing a new full version of their app every 4-5 days, as determined in this year's SmartBear State of Software Quality | Application Stability Index report ...